Object scale selection of hierarchical image segmentation with deep seeds-Reference-Cited by-同舟云学术

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Object scale selection of hierarchical image segmentation with deep seeds

Published:2020-12-06 Issue:1 Volume:15 Page:191-205
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET image process

Author:

Al‐Huda Zaid¹²^ORCID,Peng Bo¹²,Yang Yan¹²,Algburi Riyadh Nazar Ali³

Affiliation:

1. School of Information Science and Technology Southwest Jiaotong University Chengdu Sichuan China

2. National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu Sichuan China

3. School of Mechanical Engineering Southwest Jiaotong University Chengdu Sichuan China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/ipr2.12020

Reference62 articles.

1. Hierarchical Segmentation Evaluation of Region-Based Image Hierarchy

2. Weakly-Supervised Image Semantic Segmentation Based on Superpixel Region Merging

3. Supervised image segmentation based on superpixel and improved normalised cuts

4. Hierarchical Image Segmentation Based on Iterative Contraction and Merging

5. Alghodhaifi H. Lakshmanan S.: Simulation‐based model for surrogate safety measures analysis in automated vehicle‐pedestrian conflict on an urban environment. In: Autonomous Systems: Sensors Processing and Security for Vehicles and Infrastructure 2020 vol. 11415 pp. 1141504. SPIE Bellingham WA (2020)

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